SAS® Forecasting for Desktop

Plan confidently with reliable, automatically generated forecasts

Automatically generate forecasts to help you plan more efficiently and effectively. Included are a complete model repository with a full range of forecasting methods, automated statistical forecast model selection and parameter optimization, hierarchical reconciliation, event modeling, what-if analysis and scenario planning.

Benefits

Get reliable forecasts – no programming required.

Across multiple products and locations – at all levels of aggregation – the solution builds appropriate models for your data while minimizing the opportunity for errors due to human intervention, bias or lack of expertise.

Make faster, better decisions with manageable forecasting processes.

An easy-to-manage forecasting process enables analysts to focus on the most important forecasts and on other value-added analysis and reporting tasks.

Plan future events more realistically.

Based on variables you supply in the modeling process, the software automatically selects variables (e.g., business drivers, holidays or events) to generate forecasts that reflect the intricacies of your business.

Assess forecast uncertainty and risk.

Instead of a point forecast, the solution provides a statistical and visual range of likely outcomes, enabling you to assess forecast uncertainty and risk, and make decisions accordingly.

Empower users of all skill levels.

A convenient, wizard-driven interface gives novice users access to state-of-the-art forecasting methods without programming or knowledge of time series models. At the same time, the solution has all the power and sophistication that more experienced analysts need.

Screenshots

SAS Forecast Studio Interface

Exceptions & High-Value Forecasts

Forecast Plot

Features

Automatic forecasting. Generates statistically sound forecasts for up to 1,000 time series per project without the need for human intervention

Scalability and modeling. Lets you create multiple projects (by product family, brand, sales, etc.) if there are more than 1,000 time series to forecast.